What is the Importance of the Integration of Big Data and Data Science?

Data has to be dealt with by every business. Successful management and analysis of data can determine the future of an organization. But it needs a fair amount of initial investments and it is not very easy to understand the true data needs of a company. The large scale businesses that have put data to great use to get ahead of their competitors have inspired businesses of all scales to build data insight strategies but success is not always imminent. A very basic and usual shortcoming in a company’s data strategy is failing to identify the distinction between big data and data science. These can be called two radically different sides of the same coin that need distinctive treatment.

The conceptual difference

Data science deals with everything related to data cleansing, preparation and analysis. Data science builds the models that move data from raw to relevant. It adds value to the great amounts of collected data.

Big data on the other hand refers to the humongous amount of data that is collected and managed through various sources and needs to be dealt with in order to draw important insights.

The different fields

Both Big data and data science have individual roles in various fields.

Data science holds direct relevance with

Digital advertisements

Internet searches

Search recommendations

Big data is more important in fields such as

Financial services

Tele communication

Retail

Ecommerce

We can theoretically segregate big data and data science in respect to generalized concepts and for certain fields. This generalization can be fatal for new enterprises that are only just forming a data strategy and getting ready to make fresh investments on it. Big data and data science need different approaches but they work best when they are integrated and used as big data science.

Big data science – The integration of two giants

According to an article by Forbes we are moving toward an age when every human being on the planet will create 1.7 megabytes of data every second. We live in a connected world; we add data to the web with our every activity. Companies are desperate to leverage the data from all available sources to improve conversion rates, product design and customer experience. The consumer base is expanding and so is the number of peers for each company. The only way of survival is staying ahead of time and to do that the big data and data science industries are growing at an unconceivable pace. This is a time when every mistake can cost you a fortune.

It is important that you know your requirements and understand the measure that need to be taken in order to fulfill those requirements. Messing up between big data and data science is the worst mistake that one can commit but using one and staying completely away from the other is just as bad.

You need to integrate the two giants. Make them work together.

Use data science algorithms to identify and analyze the relevant datasets.

Use big data tools to streamline huge amount of data and analyze it.

Together they are stronger

The amount of resources and time assigned to each field will depend on the scale, market and consumer base of the business. To be honest no business today has a completely unique model. A manufacturing unit may well use the same digital marketing policies as a service based software network. Toward the beginning of the article there is a section that explains the different roles of big data and data science; a closer scrutiny should tell you that none works without the other.

How many retailing chains can you find, which do not use search engine optimization and digital advertisements? Not too many, I’m sure. The whole generation is looking at the mobile and the tablet screens, popping up there is the most plausible way to make an impression on their mind. But you cannot just invest a huge amount of money and appear before a large number of audiences whenever they open a certain web page; it is not only unaffordable but unreasonable as well. Data Science comes into play to tell you which set of individuals to target at what time. Data science algorithms help you to optimize every detail of a digital ad in accordance with the people it is addressed to. More importantly it identifies the right set of people for you. This is just a small example of the numerous things that data science can do for you. You cannot really leave out machine learning while talking about all these. Though it is a different topic altogether but when integrated with data science it can do wonders for you – say predict the object your customer will wish to buy next.

Big data science has changed many fortunes. It is the most potent weapon that a business of any scale can use to earn a competitive edge. IT, Finance, Healthcare, Manufacturing, and Military, all the industries are becoming data centric creating hundreds of thousands jobs around the globe. There was never a better time to be a part of the world of big data science.

6 thoughts on “What is the Importance of the Integration of Big Data and Data Science?”

I am planning to do the combo Data Science using SAS and R and Certified Big Data Expert starting from 22nd January 2017 by AnalytixLabs.
I come from SAP (ERP) Functional consultant background and planning to move to Business Analytics(Or Business Intelligence or Data Science or Data Analyst or Big Data Expert really not sure what to use here but yes I do have interest in getting insights from data by analysing it by any means).
I was searching for jobs in naukri.com and other job portals based upon these 2 courses provided in combo.
What I found was that job requirement is either of SAS,R (Data Science)or Big Data expert on Hadoop with Hive,pig,etc.
With the business perspective, this article taught me that both Data Science as well as Big Data are required for success of business.
But with job perspective, are these 2 different career lines?
If I learn these 2 courses and in the end, one of the course will be only knowledge for me and not an edge in getting a job?
I am not understating any one’s importance here. I am new to this field and want to learn thoroughly the concepts,tools,techniques and give next 6 months for this course but I am not sure what kind of job role I would go for after doing this course. It will be great if someone helps me out here.